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Why Data Science and Data Visualization are Important for Future Highway Asset Management?

Why Data Science and Data Visualization are Important for Future Highway Asset Management?

Hardly a day goes by without hearing the importance of data: “data is the new gold!”, “data is the new black gold!”… As you can see, knowing how to properly exploit data at your disposal has become critical for almost all sectors.

“…If the first to recruit are from digital services, banking and insurance, the health sector is not left with the desire to see the emergence of a predictive, preventive, personalized and participatory medicine. Eventually the phenomenon will extend to the entire industrial sector: transport, energy, nuclear…” 

Highway asset management is no exception in digital transformation, it is no longer exclusively for people who love asphalt and concrete, it can be a fulfilling career for creative types as well.
The concept of digital transformation in highway asset management is not new. Transportation authorities around the world has been making the transition from manual to fully automated network highway condition data collection to assess overall health of highway network and for asset management purposes.
But the data issues have been greatly amplified in recent years as the technologies become increasingly sophisticated.  Transportation authorities need to keep pace with the increasing data volumes and complexity in data types from the transportation Big Data sources“generated by sensors and data collection points from passenger counting systems, vehicle location systems, ticketing and fare collection systems, and scheduling and asset management systems.” To continue support pavement management decisions, it therefore becomes imperative to be able to quickly visualize and analyze these huge amounts of pavement data.

What does this mean for transportation authorities?
When the traditional engineering meets the digital transformation, what does this mean to the transportation authorities? It means that the authorities are able to keep the roads healthier and safer by knowing more about our road condition, making better decision on operation investment, and developing better plans for road maintenance, as long as we know how to use this data correctly.
Today, no one can afford to leave the data solely in the hands of a few experts, formerly reserved for users who master the technical tools. Data analysis and visualization solutions must now go through all hands to enable a 360-degree view of our activities and a better responsiveness to all aspects of the business.
Unsurprisingly, this shift also sharply raises expectations of the data ability to deliver detailed, accurate reports to support new business models and investment strategies.

What are the challenges?
1. Obsolete tools
In parallel with the digital transformation, we can still see that many organizations do not have the means at their disposal to allow everyone to access analytics to drive their business.
2. A problem of evolution
Many organizations are still reluctant to change the historical tools that were implemented many years ago. However, these tools no longer allow users to respond to requests. Often, managers who cannot use them are dependent on a third party to build their reports and access key indicators. It is a waste of time that affects the responsiveness of the organization.
3. Unfulfilled promises
Others have chosen new generation of Business Intelligence (BI) tools that promise a better user experience. This is a good idea in theory, however, in practice, most solutions are inadequate and do not allow a user without technical knowledge to create a dashboard on its activities on demand.
4. Organizations are still “beginners”
Some organizations are not yet properly equipped and continue to use tools like Excel in most of their departments. These tools can be very effective at first. But they become heavy and time-consuming when you start wanting to do analyzes on different data sources or when you want to have a global and shared view of the organization’s activities.

Why data science and data visualization is Important?
Following are the top 5 reasons to take advantage of data visualization for pavement management:
1. Benefit from a new, more efficient way of transmitting and assimilating information
Generally, asset management information compiled by the technical teams includes static charts and graphs. Transforming this approach to web-based data visualization is more likely to find new ways to interpret data. Both the technical and management teams will find the information they need more easily and are more productive.
2. Find links and trends between different highway data
By facilitating correlations, data visualization allows the asset management team to identify problem sources faster and act faster to resolve them. The data can also be compared quickly and easily.
3. Respond more quickly to highway condition deterioration
Highway condition indicators can be used to discover changes on highway condition. Being able to visualize these indicators are critical for investment decision-making on highway assets as it allows organizations to capture highway condition deterioration over time.
4. Interact directly with the data
Data visualization tools not only allow you to see the highway asset data, but also to manipulate and interact with it. The most effective actions can therefore be put forward based on analytical models developed through visualization and predictive analytics.
5. Tell compelling stories
Data visualization can engage management teams towards the highway data results in greater performance. The way the pavement data accessible to all will enable both technical and management team to tell a story through the data.

Link: Why Data Science and Data Visualization are Important for Future Highway Asset Management?